AB1602 CROSS COUNTRY DIFFERENCES IN B/TSDMARD PRESCRIPTION BEHAVIOR: ASSOCIATIONS BETWEEN SOCIOECONOMICS, REAL WORLD B/TSDMARD USE AND DISEASE OUTCOMES
Authors: I. Nevins, D. Courvoisier, A. Finckh, R. Fritsch-Stork, D. Nordström, A. M. Rodrigues, Ș. C. Dinescu, Á. García Martos, M. Oztas, Z. Rotar, K. Solomon-Escoto, A. Chopra, D. Vega-Morales, P. D. De Buck, D. Choquette, R. Conway, F. Iannone, C. Allaart, T. Huizinga, K. Lauper, S. A. Bergstra
Journal: Annals of the Rheumatic Diseases (2023)

<h3>Background</h3> The development of biologic and targeted synthetic (b/ts)DMARDs contributed to improved treatment outcomes in rheumatoid arthritis (RA). However, high medications costs may limit their use. Previously we showed that in countries with a lower socioeconomic status (SES), b/tsDMARDs were prescribed to fewer patients than in countries with higher SES. In this study we take a more detailed look at b/tsDMARD prescription behavior between countries. <h3>Objectives</h3> To explore cross-country relationships between Gross Domestic Product (GDP) per capita, specific indicators of b/tsDMARDs use and disease outcomes in patients with RA. <h3>Methods</h3> This multinational, observational study included countries that had contributed ≥100 patients using b/tsDMARDs, with available follow up, to one of 2 registries: METEOR, an international registry capturing daily clinical practice data of patients with a clinical diagnosis of RA, and JAK-POT, an investigator-initiated collaboration between national registries aiming to evaluate clinical aspects of b/tsDMARDs in RA. On a per-country basis, mean DAS28 was calculated from the last available follow-up visit per patient. b/tsDMARD usage was determined as mean time to start b/tsDMARD therapy since date of diagnosis, mean number of b/tsDMARDs tried per patient and mean duration of b/tsDMARD therapy. To calculate the time to start a first b/tsDMARD per country included from the JAK-POT registry, only bionaïve patients were included. Possible associations between GDP per capita and country-level indicators of b/tsDMARD use and DAS28 were tested in univariable linear regression models. Regression coefficients (β) are interpreted as the numerical increase in the outcome per 1 point increase in the predictor. <h3>Results</h3> Data from 25,832 patients living in 17 different countries showed varying b/tsDMARD prescription behavior. GDP per capita ranged from 6505 (India) to 93350 Intl$ (Ireland). Time to start b/tsDMARD therapy ranged from 0.5 (Austria) to 11.1 (Finland) years. Mean number of b/tsDMARDs tried per patient ranged from 1.0 (Turkey) to 2.4 (Switzerland). Duration of b/tsDMARD therapy ranged from 0.9 (India) to 5.5 (Portugal) years (Figure 1). Baseline DAS28 ranged between 3.7 and 6.1, but was not related to any of the indicators of b/tsDMARD use: time to start a b/tsDMARD β 0.08 (95% CI -0.7; 0.9), number of prescribed b/tsDMARDs β 0.06 (95% CI -0.03; 0.2), duration of b/tsDMARD treatment β 0.1 (95% CI -0.3; 0.5). No statistically significant associations were observed between GDP per capita and time to start b/tsDMARD therapy (Figure 1A, β 0.09 CI 95% -0.7; 0.9), the number of b/tsDMARDs tried per patient (fig 1B, β 0.07 CI 95% -0.02; 0.2) or the duration of b/tsDMARD treatment (fig 1C, β 0.1 CI 95% -0.3; 0.5). None of the indicators of b/tsDMARD prescription were significantly related to DAS28 at the end of follow up: time to start a b/tsDMARD β 0.02 (95% CI -0.05; 0.1), duration of b/tsDMARD therapy β -0.03 (95% CI -0.2; 0.1) and number of b/tsDMARDs β -0.03 (95% CI -0.6; 0.6). <h3>Conclusion</h3> This study showed varying b/tsDMARD prescription behavior and disease activity across 17 countries worldwide. Overall, differences in b/tsDMARD prescription behaviour did not appear to be related to socioeconomic welfare and, no significant association was observed between b/tsDMARD prescription behavior and disease activity at a country level. This seems to indicate that once patients start a b/tsDMARD, socioeconomic welfare has less impact on b/tsDMARD use. <h3>REFERENCES:</h3> NIL. <h3>Acknowledgements:</h3> NIL. <h3>Disclosure of Interests</h3> Isabell Nevins: None declared, Delphine Courvoisier: None declared, Axel Finckh Speakers bureau: AbbVie, BMS, Pfizer, Eli-Lilly, Sandroz, Consultant of: AbbVie, Novartis, Pfizer, MSD, Lilly, Grant/research support from: AbbVie, BMS, Galapagos, Lilly, Pfizer, Ruth Fritsch-Stork: None declared, Dan Nordström: None declared, Ana Maria Rodrigues: None declared, ȘTEFAN CRISTIAN DINESCU: None declared, Álvaro García Martos: None declared, Mert Oztas: None declared, Ziga Rotar: None declared, Karen Solomon-Escoto: None declared, Arvind Chopra: None declared, David Vega-Morales: None declared, Petronella DM de Buck: None declared, Denis Choquette: None declared, Richard Conway Speakers bureau: Janssen, Roche, Sanofi, AbbVie, Galapagos, Fresenius Kabi, Viatris, Grant/research support from: Janssen, Celltrion, Nordic Pharma, Abbvie, Florenzo Iannone: None declared, Cornelia Allaart: None declared, Thomas Huizinga: None declared, Kim Lauper: None declared, Sytske Anne Bergstra Grant/research support from: ASPIRE grant from Pfizer.